Particle Swarm Thread Scheduling for Parallelizable Dependent Tasks in Heterogeneous Grid Environment

Scheduling workloads is a difficult task. In order to design efficient scheduling algorithms for dependent workloads, it is required to have a good in-depth knowledge of basic scheduling strategies and graph theory. This paper analyzes the distribution of sequential dependent tasks and the scheduling behavior in heterogeneous computational grid environments. In this paper, we also propose a new thread based algorithm for scheduling dependent tasks and optimize the algorithm using heuristic principles. Introducing Particle swarm based Thread parallel Scheduling; we have successfully demonstrated a new heuristic algorithm for scheduling of dependent tasks. Experiments prove the increased performance and efficiency after incorporation of the optimization techniques.